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Weak Convergence Limits for Closed Cyclic Networks of Queues with Multiple Bottleneck Nodes

Published online by Cambridge University Press:  04 February 2016

Ole Stenzel*
Affiliation:
University of Hamburg
Hans Daduna*
Affiliation:
University of Hamburg
*
Current address: Institute of Stochastics, Ulm University, Helmholtzstrasse 18, 89069 Ulm, Germany.
∗∗ Postal address: Center of Mathematical Statistics and Stochastic Processes, University of Hamburg, Bundesstrasse 55, 20146 Hamburg, Germany. Email address: [email protected]
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Abstract

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We consider a sequence of cycles of exponential single-server nodes, where the number of nodes is fixed and the number of customers grows unboundedly. We prove a central limit theorem for the cycle time distribution. We investigate the idle time structure of the bottleneck nodes and the joint sojourn time distribution that a test customer observes at the nonbottleneck nodes during a cycle. Furthermore, we study the filling behaviour of the bottleneck nodes, and show that the single bottleneck and multiple bottleneck cases lead to different asymptotic behaviours.

MSC classification

Type
Research Article
Copyright
© Applied Probability Trust 

References

Bickel, P. J. and Doksum, K. A. (1977). Mathematical Statistics: Basic Ideas and Selected Topics. Prentice-Hall.Google Scholar
Boxma, O. J. (1983). The cyclic queue with one general and one exponential server. Adv. Appl. Prob. 15, 857873.Google Scholar
Boxma, O. J. (1988). Sojourn times in cyclic queues - the influence of the slowest server. In Computer Performance and Reliability, eds Iazeolla, G., Courtois, P.-J. and Boxma, O. J.. North-Holland, Amsterdam, pp. 1324.Google Scholar
Boxma, O. J., Kelly, F. P. and Konheim, A. G. (1984). The product form for sojourn time distributions in cyclic exponential queues. J. Assoc. Comput. Mach. 31, 128133.Google Scholar
Burke, P. J. (1968). The output process of a stationary M/{M}/s queueing system. Ann. Math. Statist. 39, 11441152.Google Scholar
Burke, P. J. (1969). The dependence of sojourn times in tandem M/M/s queues. Operat. Res. 17, 754755.Google Scholar
Chow, W. M. (1980). The cycle time distribution of exponential cyclic queues. J. Assoc. Comput. Mach. 27, 281286.Google Scholar
Daduna, H. (1984). Burke's theorem on passage times in Gordon–Newell networks. Adv. Appl. Prob. 16, 867886.Google Scholar
Daduna, H. and Szekli, R. (2002). Conditional Job-observer property for multitype closed queueing networks. J. Appl. Prob. 39, 865881.Google Scholar
Daduna, H., Malchin, C. and Szekli, R. (2008). Weak convergence limits for sojourn times in cyclic queues under heavy traffic conditions. J. Appl. Prob. 45, 333346.Google Scholar
Gordon, W. J. and Newell, G. F. (1967). Closed queueing networks with exponential servers. Operat. Res. 15, 254265.Google Scholar
Harrison, P. G. (1985). On normalizing constants in queueing networks. Operat. Res. 33, 464468.Google Scholar
Harrison, P. G. (1990). Laplace transform inversion and passage-time distributions in Markov processes. J. Appl. Prob. 27, 7487.Google Scholar
Kelly, F. P. (1984). The dependence of sojourn times in closed queueing networks. In Mathematical Computer Performance and Reliability, eds Iazeolla, G., Courtois, P.-J. and Hordijk, A., North-Holland, Amsterdam, pp. 111121.Google Scholar
Malchin, C. (2008). Stochastic networks: discrete and continuous time models. , Department of Mathematics, University of Hamburg.Google Scholar
Schassberger, R. and Daduna, H. (1987). Sojourn times in queuing networks with multiserver nodes. J. Appl. Prob. 24, 511521.CrossRefGoogle Scholar
Stenzel, O. and Daduna, H. (2009). Weak convergence limits for closed cyclic networks of queues with multiple bottleneck nodes. Preprint 2009-05, Mathematische Statistik und Stochastische Prozesse, Fachbereich Mathematik der Universität Hamburg, 22 pp.Google Scholar
Serfozo, R. F. (1999). Introduction to Stochastic Networks (Appl. Math. 44). Springer, New York.Google Scholar